International survey shows modest AI impact in pediatric radiology; bone age assessment is top application

In a survey of 18 international pediatric radiology centres (69% response), 88.9% deployed ≥1 AI tool, most commonly bone age assessment (44.4%). Mean clinical impact was 3.56/5; only 16.7% rated AI as transformational. The top barrier: lack of pediatric-specific datasets (83.3%…

• Cross-sectional survey of 18 paediatric radiology centres globally (69% response rate) using a 14-item questionnaire.
• Other top barriers: integration challenges (66.7%), high cost/unclear ROI (50%), cybersecurity concerns (44.4%); enablers included vendor maturity (72.2%) and internal champions (66.7%).
• A majority (55.6%) agreed that pediatric AI research overemphasizes model development over clinical integration, ethics, and sustainability.

Cross-sectional survey design with 18 centres (69% response) and self-reported leadership perspective may introduce selection and reporting bias; full article text not reviewed.

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